Link to the Hogwarts house program.
library(shiny)
shinyUI(pageWithSidebar(
headerPanel("Hogwarts House Selection"),
sidebarPanel(
selectInput("house","Select your main trait",
choices = c("Brave", "Cunning", "Loyal", "Intelligent"))
),
mainPanel(
h3('Your House is:'),
verbatimTextOutput("selected_house")
)))
shinyServer(function(input, output){
Hogwarts_house <- reactive({
switch(input$house,
"Brave" = "Gryffindor",
"Cunning" = "Slytherin",
"Loyal" = "Hufflepuff",
"Intelligent" = "Ravenclaw")
})
output$selected_house<- renderPrint(Hogwarts_house())
})
dat_class= read.table("https://raw.githubusercontent.com/bcaffo/ds4bme/master/data/classInterests.txt", header=TRUE)
library(ggplot2)
library(plotly)
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
## The following object is masked from 'package:stats':
##
## filter
## The following object is masked from 'package:graphics':
##
## layout
class_plot <- ggplot(dat_class,aes(x=Year,fill= Program))
class_plot = class_plot + geom_bar()
ggplotly(class_plot)
library(ggmosaic)
dat_class= read.table("https://raw.githubusercontent.com/bcaffo/ds4bme/master/data/classInterests.txt", header=TRUE)
mosaic_class <- ggplot(data=dat_class) +
geom_mosaic(aes(x=product(Year), fill = Program))
ggplotly(mosaic_class)
dat_health= read.csv("https://raw.githubusercontent.com/jhu-advdatasci/2018/master/data/KFF/healthcare-spending.csv", skip=2)
dat_health_states <- dat_health[-c(1,53:61),]
library(reshape)
##
## Attaching package: 'reshape'
## The following object is masked from 'package:plotly':
##
## rename
health_states_melt <- melt(dat_health_states, id.vars = "Location")
health_plot <- ggplot(health_states_melt,aes(x=variable, y=value, group= Location, color=Location))
health_plot = health_plot + geom_line()
health_plot = health_plot + theme(axis.text.x = element_text(angle = 90))
ggplotly(health_plot)
avg<- rowMeans(dat_health_states[,-1])
health_states_avg <- data.frame(Location=dat_health_states[,1], Spending= avg)
health_barplot <- ggplot(health_states_avg, aes(x=Location, y=Spending))
health_barplot <- health_barplot + geom_col()
health_barplot = health_barplot + theme(axis.text.x = element_text(angle = 90))
ggplotly(health_barplot)
Link to the BMI calculator program.
shinyUI(
pageWithSidebar(
headerPanel("BMI Calculator"),
sidebarPanel(
numericInput('height', 'Height (in)', 65, min=0, step = 1),
numericInput('weight', 'Weight (lbs)', 150, min=0, step = 1),
submitButton('Submit')
),
mainPanel(
h3('BMI- Results'),
h4('Height you entered'),
verbatimTextOutput("input_height"),
h4('Weight you entered'),
verbatimTextOutput("input_weight"),
h4('Calculated BMI'),
verbatimTextOutput("BMI_output")
)))
BMI_calculator <- function(height, weight) (weight/(height)^2)*703
shinyServer(
function(input, output) {
output$input_height <- renderPrint({input$height})
output$input_weight <- renderPrint({input$weight})
output$BMI_output <- renderPrint({BMI_calculator(input$height, input$weight)})
}
)